Search result for Probability and statistics course online Online Courses & Certifications
FollowFilter ![]()
Filter ![]()
Showing 340 courses
By Category ![]()
By Subject![]()
By Language![]()
By Duration![]()
By Price![]()
Get Course Alerts by Email
Specialized Models: Time Series and Survival Analysis
by Mark J Grover , Miguel Maldonado- 4.5
-
![]()
![]()
![]()
![]()
![]()
Approx. 11 hours to complete
This course introduces you to additional topics in Machine Learning that complement essential tasks, including forecasting and analyzing censored data. The hands-on section of this course focuses on using best practices and verifying assumptions derived from Statistical Learning. This course targets aspiring data scientists interested in acquiring hands-on experience with Time Series Analysis and Survival Analysis....
Supervised Learning: Regression
by Mark J Grover , Miguel Maldonado- 4.8
-
![]()
![]()
![]()
![]()
![]()
Approx. 11 hours to complete
This course introduces you to one of the main types of modelling families of supervised Machine Learning: Regression. You will learn how to train regression models to predict continuous outcomes and how to use error metrics to compare across different models. This course also walks you through best practices, including train and test splits, and regularization techniques....
Supervised Machine Learning: Regression
by Mark J Grover , Miguel Maldonado- 4.7
-
![]()
![]()
![]()
![]()
![]()
Approx. 11 hours to complete
This course introduces you to one of the main types of modelling families of supervised Machine Learning: Regression. You will learn how to train regression models to predict continuous outcomes and how to use error metrics to compare across different models. This course also walks you through best practices, including train and test splits, and regularization techniques....
Math in Sports
by Anne Pilkington , Michael Hildreth- 0.0
-
![]()
![]()
![]()
![]()
![]()
4 Weeks
In this course you will learn to use some mathematical tools that can help predict and analyze sporting performances and outcomes. This course will help coaches, players, and enthusiasts to make educated decisions about strategy, training, and execution. How a basic understanding of probability and statistics can be used to analyze sports and other real life situations....
$50
Computational Probability and Inference
by George H. Chen , Polina Golland , Gregory W. Wornell , Lizhong Zheng- 0.0
-
![]()
![]()
![]()
![]()
![]()
12 Weeks
Learn fundamentals of probabilistic analysis and inference. Probability and inference are used everywhere. In this data analysis and computer programming course, you will learn the principles of probability and inference. You don’t need to have prior experience in either probability or inference, but you should be comfortable with basic Python programming and calculus....
$49
Unsupervised Learning
by Mark J Grover , Miguel Maldonado- 4.9
-
![]()
![]()
![]()
![]()
![]()
Approx. 9 hours to complete
This course introduces you to one of the main types of Machine Learning: Unsupervised Learning. The hands-on section of this course focuses on using best practices for unsupervised learning. This course targets aspiring data scientists interested in acquiring hands-on experience with Unsupervised Machine Learning techniques in a business setting. Introduction to Unsupervised Learning and K Means Course Introduction...
Unsupervised Machine Learning
by Mark J Grover , Miguel Maldonado- 4.8
-
![]()
![]()
![]()
![]()
![]()
Approx. 9 hours to complete
This course introduces you to one of the main types of Machine Learning: Unsupervised Learning. The hands-on section of this course focuses on using best practices for unsupervised learning. This course targets aspiring data scientists interested in acquiring hands-on experience with Unsupervised Machine Learning techniques in a business setting. Introduction to Unsupervised Learning and K Means Course Introduction...
Related searches
Guided Tour of Machine Learning in Finance
by Igor Halperin- 3.8
-
![]()
![]()
![]()
![]()
![]()
Approx. 24 hours to complete
This course aims at providing an introductory and broad overview of the field of ML with the focus on applications on Finance. Simultaneously, while this course can be taken as a separate course, it serves as a preview of topics that are covered in more details in subsequent modules of the specialization Machine Learning and Reinforcement Learning in Finance....
Inferential Statistical Analysis with Python
by Brenda Gunderson , Brady T. West , Kerby Shedden- 4.6
-
![]()
![]()
![]()
![]()
![]()
Approx. 19 hours to complete
In this course, we will explore basic principles behind using data for estimation and for assessing theories. We will analyze both categorical data and quantitative data, starting with one population techniques and expanding to handle comparisons of two populations. Language and Notation The Python Statistics Landscape Functions and Lambda Functions, Reading Help Files...
Pricing Options with Mathematical Models
by Jaksa Cvitanic- 0.0
-
![]()
![]()
![]()
![]()
![]()
10 Weeks
Introduction to the Black-Scholes-Merton model and other mathematical models for pricing financial derivatives and hedging risk in financial markets. This is an introductory course on options and other financial derivatives, and their applications to risk management. You should have a working knowledge of basic calculus, statistics, and probability and be interested in the use of mathematical modeling....
$49
Previous
